Advertisement

Runs in the Family

The power to detect mutations involved in disease by genome sequencing is enhanced when combined with the ability to discover specific mutations that may have arisen between offspring and parents. Roach et al. (p. 636, published online 10 March) present the sequence of a family with two offspring affected with two genetic disorders: Miller syndrome and primary ciliary dyskinesia. Sequence analysis of the children and their parents not only showed that the intergenerational mutation rate was lower than anticipated but also revealed recombination sites and the occurrence of rare polymorphisms.

Abstract

We analyzed the whole-genome sequences of a family of four, consisting of two siblings and their parents. Family-based sequencing allowed us to delineate recombination sites precisely, identify 70% of the sequencing errors (resulting in > 99.999% accuracy), and identify very rare single-nucleotide polymorphisms. We also directly estimated a human intergeneration mutation rate of ~1.1 × 10−8 per position per haploid genome. Both offspring in this family have two recessive disorders: Miller syndrome, for which the gene was concurrently identified, and primary ciliary dyskinesia, for which causative genes have been previously identified. Family-based genome analysis enabled us to narrow the candidate genes for both of these Mendelian disorders to only four. Our results demonstrate the value of complete genome sequencing in families.

Get full access to this article

View all available purchase options and get full access to this article.

Supplementary Material

File (roach-som.pdf)

References and Notes

1
Drmanac R., et al., Human genome sequencing using unchained base reads on self-assembling DNA nanoarrays. Science 327, 78 (2010).
2
Roach J. C., Boysen C., Wang K., Hood L., Pairwise end sequencing: A unified approach to genomic mapping and sequencing. Genomics 26, 345 (1995).
3
Watterson G. A., On the number of segregating sites in genetical models without recombination. Theor. Popul. Biol. 7, 256 (1975).
4
Materials and methods are available as supporting material on Science Online.
5
Donnelly K. P., The probability that related individuals share some section of genome identical by descent. Theor. Popul. Biol. 23, 34 (1983).
6
Kruglyak L., Daly M. J., Reeve-Daly M. P., Lander E. S., Parametric and nonparametric linkage analysis: A unified multipoint approach. Am. J. Hum. Genet. 58, 1347 (1996).
7
Abecasis G. R., Cherny S. S., Cookson W. O., Cardon L. R., Merlin—Rapid analysis of dense genetic maps using sparse gene flow trees. Nat. Genet. 30, 97 (2002).
8
Petkov P. M., Broman K. W., Szatkiewicz J. P., Paigen K., Crossover interference underlies sex differences in recombination rates. Trends Genet. 23, 539 (2007).
9
Chimpanzee Sequencing and Analysis Consortium, Initial sequence of the chimpanzee genome and comparison with the human genome. Nature 437, 69 (2005).
10
Nachman M. W., Crowell S. L., Estimate of the mutation rate per nucleotide in humans. Genetics 156, 297 (2000).
11
Haile-Selassie Y., Late Miocene hominids from the Middle Awash, Ethiopia. Nature 412, 178 (2001).
12
Haile-Selassie Y., Asfaw B., White T. D., Hominid cranial remains from upper Pleistocene deposits at Aduma, Middle Awash, Ethiopia. Am. J. Phys. Anthropol. 123, 1 (2004).
13
Haile-Selassie Y., Suwa G., White T. D., Late Miocene teeth from Middle Awash, Ethiopia, and early hominid dental evolution. Science 303, 1503 (2004).
14
Deino A. L., Tauxe L., Monaghan M., Hill A., 40Ar/(39)Ar geochronology and paleomagnetic stratigraphy of the Lukeino and lower Chemeron Formations at Tabarin and Kapcheberek, Tugen Hills, Kenya. J. Hum. Evol. 42, 117 (2002).
15
Brunet M., et al., A new hominid from the Upper Miocene of Chad, Central Africa. Nature 418, 145 (2002).
16
Chen F. C., Li W. H., Genomic divergences between humans and other hominoids and the effective population size of the common ancestor of humans and chimpanzees. Am. J. Hum. Genet. 68, 444 (2001).
17
Burgess R., Yang Z., Estimation of hominoid ancestral population sizes under bayesian coalescent models incorporating mutation rate variation and sequencing errors. Mol. Biol. Evol. 25, 1979 (2008).
18
Takahata N., Relaxed natural selection in human populations during the Pleistocene. Jpn. J. Genet. 68, 539 (1993).
19
J. D. Wall, Estimating ancestral population sizes and divergence times. Genetics 163, 395 (2003). [Abstract/Free Full Text]
20
Kondrashov A. S., Direct estimates of human per nucleotide mutation rates at 20 loci causing Mendelian diseases. Hum. Mutat. 21, 12 (2003).
21
Xue Y., et al., Human Y chromosome base-substitution mutation rate measured by direct sequencing in a deep-rooting pedigree. Curr. Biol. 19, 1453 (2009).
22
Ng S. B., et al., Exome sequencing identifies the cause of a mendelian disorder. Nat. Genet. 42, 30 (2010).
23
Olbrich H., et al., Mutations in DNAH5 cause primary ciliary dyskinesia and randomization of left-right asymmetry. Nat. Genet. 30, 143 (2002).
24
Ng S. B., et al., Targeted capture and massively parallel sequencing of 12 human exomes. Nature 461, 272 (2009).
25
Choi M., et al., Proc. Natl. Acad. Sci. U. S. A. 106, 190961 (2009).

(0)eLetters

eLetters is a forum for ongoing peer review. eLetters are not edited, proofread, or indexed, but they are screened. eLetters should provide substantive and scholarly commentary on the article. Embedded figures cannot be submitted, and we discourage the use of figures within eLetters in general. If a figure is essential, please include a link to the figure within the text of the eLetter. Please read our Terms of Service before submitting an eLetter.

Log In to Submit a Response

No eLetters have been published for this article yet.

Information & Authors

Information

Published In

Science
Volume 328 | Issue 5978
30 April 2010

Article versions

You are viewing the most recent version of this article.

Submission history

Received: 7 January 2010
Accepted: 5 March 2010
Published in print: 30 April 2010

Permissions

Request permissions for this article.

Acknowledgments

This study was supported by the University of Luxembourg–Institute for Systems Biology Program and by these NIH grants: Center for Systems Biology GM076547 (L.H. and L.R.), RO1GM081083 (A.F.S. and G.G.), R01HL094976 and RZ1HG004749 (J.S.), RC2HG005608 (M.D. and J.S.), and R01HD048895 (M.B.). H. Tabor assisted with ethical review. J. Xing performed the principal components analysis. H. Mefford performed CNV analysis. A. Bigham and K. Buckingham evaluated candidate genes in unrelated individuals. D. Ballinger, A. Sparks, A. Halpern, and G. Nilsen assisted with sequencing and analysis. R. Bressler, S. Dee, and D. Mauldin assisted with bioinformatics. S. Ng and R. Qiu performed the capture array. S. Bloom obtained the resequencing data on the Illumina Genome Analyzer. M. Janer and S. Li performed Sequenom analysis. D. Cox commented on an early version of the manuscript. R. Durbin and D. Altshuler granted permission for our use of 1000 genomes SNP data. CGI employees (R.D. and K.P.) have stock options in the company. J.S. has consulted for CGI. L.H. is a scientific advisor to CGI and holds stock in the company. The dbGAP accessions can be found at www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000244.v1.p1 (accession phs000244.v1.p1).

Authors

Affiliations

Jared C. Roach*
Institute for Systems Biology, Seattle, WA 98103, USA.
Gustavo Glusman*
Institute for Systems Biology, Seattle, WA 98103, USA.
Arian F. A. Smit*
Institute for Systems Biology, Seattle, WA 98103, USA.
Chad D. Huff*
Institute for Systems Biology, Seattle, WA 98103, USA.
Department of Human Genetics, Eccles Institute of Human Genetics, University of Utah, Salt Lake City, UT 84109, USA.
Robert Hubley
Institute for Systems Biology, Seattle, WA 98103, USA.
Paul T. Shannon
Institute for Systems Biology, Seattle, WA 98103, USA.
Lee Rowen
Institute for Systems Biology, Seattle, WA 98103, USA.
Krishna P. Pant
Complete Genomics, Inc. (CGI), Mountain View, CA 94043, USA.
Nathan Goodman
Institute for Systems Biology, Seattle, WA 98103, USA.
Michael Bamshad
Department of Pediatrics, University of Washington, Seattle, WA 98195, USA.
Jay Shendure
Department of Genome Sciences, University of Washington, Seattle, WA 98195, USA.
Radoje Drmanac
Complete Genomics, Inc. (CGI), Mountain View, CA 94043, USA.
Lynn B. Jorde
Department of Human Genetics, Eccles Institute of Human Genetics, University of Utah, Salt Lake City, UT 84109, USA.
Institute for Systems Biology, Seattle, WA 98103, USA.
David J. Galas [email protected]
Institute for Systems Biology, Seattle, WA 98103, USA.

Notes

*
These authors contributed equally to this work.
To whom correspondence should be addressed. E-mail: [email protected] (D.J.G.); [email protected] (L.H.)

Metrics & Citations

Metrics

Article Usage

Altmetrics

Citations

Cite as

Export citation

Select the format you want to export the citation of this publication.

Cited by

  1. Methods to improve the accuracy of next-generation sequencing, Frontiers in Bioengineering and Biotechnology, 11, (2023).https://doi.org/10.3389/fbioe.2023.982111
    Crossref
  2. Genetics of Kidney Disease: The Unexpected Role of Rare Disorders, Annual Review of Medicine, 74, 1, (353-367), (2023).https://doi.org/10.1146/annurev-med-042921-101813
    Crossref
  3. The origins and functional effects of postzygotic mutations throughout the human life span, Science, 380, 6641, (2023)./doi/10.1126/science.abn7113
    Abstract
  4. Genome sequencing-based discovery of a novel deep intronic APC pathogenic variant causing exonization, European Journal of Human Genetics, (2023).https://doi.org/10.1038/s41431-023-01322-y
    Crossref
  5. Comparing inference under the multispecies coalescent with and without recombination, Molecular Phylogenetics and Evolution, 181, (107724), (2023).https://doi.org/10.1016/j.ympev.2023.107724
    Crossref
  6. Two germline mutations can serve as genetic susceptibility screening makers for a lung adenocarcinoma family, Journal of Cancer Research and Clinical Oncology, (2023).https://doi.org/10.1007/s00432-023-04616-2
    Crossref
  7. The Mutationathon highlights the importance of reaching standardization in estimates of pedigree-based germline mutation rates, eLife, 11, (2022).https://doi.org/10.7554/eLife.73577
    Crossref
  8. Analysis of the Whole-Genome Sequences from an Equus Parent-Offspring Trio Provides Insight into the Genomic Incompatibilities in the Hybrid Mule, Genes, 13, 12, (2188), (2022).https://doi.org/10.3390/genes13122188
    Crossref
  9. Molecular Evolutionary Rate Predicts Intraspecific Genetic Polymorphism and Species-Specific Selection, Genes, 13, 4, (708), (2022).https://doi.org/10.3390/genes13040708
    Crossref
  10. Muons, mutations, and planetary shielding, Frontiers in Astronomy and Space Sciences, 9, (2022).https://doi.org/10.3389/fspas.2022.1067491
    Crossref
  11. See more
Loading...

View Options

Check Access

Log in to view the full text

AAAS ID LOGIN

AAAS login provides access to Science for AAAS Members, and access to other journals in the Science family to users who have purchased individual subscriptions.

Log in via OpenAthens.
Log in via Shibboleth.

More options

Register for free to read this article

As a service to the community, this article is available for free. Login or register for free to read this article.

Purchase this issue in print

Buy a single issue of Science for just $15 USD.

View options

PDF format

Download this article as a PDF file

Download PDF

Full Text

FULL TEXT

Media

Figures

Multimedia

Tables

Share

Share

Share article link

Share on social media